Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins

  1. Matthew WK Wong
  2. Anbupalam Thalamuthu
  3. Nady Braidy
  4. Karen A Mather
  5. Yue Liu
  6. Liliana Ciobanu
  7. Bernhardt T Baune
  8. Nicola J Armstrong
  9. John Kwok
  10. Peter Schofield
  11. Margaret J Wright
  12. David Ames
  13. Russell Pickford
  14. Teresa Lee
  15. Anne Poljak
  16. Perminder S Sachdev  Is a corresponding author
  1. Centre for Healthy Brain Ageing, University of New South Wales, Australia
  2. The University of Adelaide, Adelaide Medical School, Discipline of Psychiatry, Australia
  3. Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Australia
  4. Mathematics and Statistics, Murdoch University, Australia
  5. Brain and Mind Centre, The University of Sydney, Australia
  6. Neuroscience Research Australia, Australia
  7. Queensland Brain Institute, University of Queensland, Australia
  8. University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Australia
  9. University of New South Wales, Australia

Abstract

The critical role of blood lipids in a broad range of health and disease states is well recognised but less explored is the interplay of genetics and environment within the broader blood lipidome. We examined heritability of the plasma lipidome among healthy older-aged twins (75 monozygotic/55 dizygotic pairs) enrolled in the Older Australian Twins Study (OATS) and explored corresponding gene expression and DNA methylation associations. 27/209 lipids (13.3%) detected by liquid chromatography-coupled mass spectrometry (LC-MS) were significantly heritable under the classical ACE twin model (h2=0.28-0.59), which included ceramides (Cer) and triglycerides (TG). Relative to non-significantly heritable TGs, heritable TGs had a greater number of associations with gene transcripts, not directly associated with lipid metabolism, but with immune function, signalling and transcriptional regulation. Genome-wide average DNA methylation (GWAM) levels accounted for variability in some non-heritable lipids. We reveal a complex interplay of genetic and environmental influences on the ageing plasma lipidome.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

The following previously published data sets were used

Article and author information

Author details

  1. Matthew WK Wong

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  2. Anbupalam Thalamuthu

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  3. Nady Braidy

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Karen A Mather

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Yue Liu

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Liliana Ciobanu

    Adelaide Medical School, The University of Adelaide, Adelaide Medical School, Discipline of Psychiatry, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Bernhardt T Baune

    Department of Psychiatry, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  8. Nicola J Armstrong

    Mathematics and Statistics, Mathematics and Statistics, Murdoch University, Perth, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4477-293X
  9. John Kwok

    Brain and Mind Centre, Brain and Mind Centre, The University of Sydney, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  10. Peter Schofield

    Faculty of Medicine, Neuroscience Research Australia, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  11. Margaret J Wright

    Queensland Brain Institute, Queensland Brain Institute, University of Queensland, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7133-4970
  12. David Ames

    Academic Unit for Psychiatry of Old Age, University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  13. Russell Pickford

    Bioanalytical Mass Spectrometry Facility, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  14. Teresa Lee

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  15. Anne Poljak

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.
  16. Perminder S Sachdev

    School of Psychiatry, Faculty of Medicine, Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
    For correspondence
    p.sachdev@unsw.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9595-3220

Funding

National Health and Medical Research Council

  • Nady Braidy
  • Perminder S Sachdev

Australian Research Council

  • Nady Braidy

Rebecca L. Cooper Medical Research Foundation

  • Nady Braidy
  • Anne Poljak
  • Perminder S Sachdev

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: OATS was approved by the Ethics Committees of the University of New South Wales and the South Eastern Sydney Local Health District (ethics approval HC17414). All work involving human participants was performed in accordance with the principles of the Declaration of Helsinki of the World Medical Association. Informed consent was obtained from all participants and/or guardians.

Copyright

© 2020, Wong et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,033
    views
  • 108
    downloads
  • 9
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Matthew WK Wong
  2. Anbupalam Thalamuthu
  3. Nady Braidy
  4. Karen A Mather
  5. Yue Liu
  6. Liliana Ciobanu
  7. Bernhardt T Baune
  8. Nicola J Armstrong
  9. John Kwok
  10. Peter Schofield
  11. Margaret J Wright
  12. David Ames
  13. Russell Pickford
  14. Teresa Lee
  15. Anne Poljak
  16. Perminder S Sachdev
(2020)
Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins
eLife 9:e58954.
https://doi.org/10.7554/eLife.58954

Share this article

https://doi.org/10.7554/eLife.58954

Further reading

    1. Chromosomes and Gene Expression
    Jake VanBelzen, Bennet Sakelaris ... Jason H Brickner
    Research Article

    Chromatin immunoprecipitation (ChIP-seq) is the most common approach to observe global binding of proteins to DNA in vivo. The occupancy of transcription factors (TFs) from ChIP-seq agrees well with an alternative method, chromatin endogenous cleavage (ChEC-seq2). However, ChIP-seq and ChEC-seq2 reveal strikingly different patterns of enrichment of yeast RNA polymerase II (RNAPII). We hypothesized that this reflects distinct populations of RNAPII, some of which are captured by ChIP-seq and some of which are captured by ChEC-seq2. RNAPII association with enhancers and promoters - predicted from biochemical studies - is detected well by ChEC-seq2 but not by ChIP-seq. Enhancer/promoter-bound RNAPII correlates with transcription levels and matches predicted occupancy based on published rates of enhancer recruitment, preinitiation assembly, initiation, elongation, and termination. The occupancy from ChEC-seq2 allowed us to develop a stochastic model for global kinetics of RNAPII transcription which captured both the ChEC-seq2 data and changes upon chemical-genetic perturbations to transcription. Finally, RNAPII ChEC-seq2 and kinetic modeling suggests that a mutation in the Gcn4 transcription factor that blocks interaction with the NPC destabilizes promoter-associated RNAPII without altering its recruitment to the enhancer.

    1. Chromosomes and Gene Expression
    2. Microbiology and Infectious Disease
    Maruti Nandan Rai, Qing Lan ... Koon Ho Wong
    Research Article Updated

    Candida glabrata can thrive inside macrophages and tolerate high levels of azole antifungals. These innate abilities render infections by this human pathogen a clinical challenge. How C. glabrata reacts inside macrophages and what is the molecular basis of its drug tolerance are not well understood. Here, we mapped genome-wide RNA polymerase II (RNAPII) occupancy in C. glabrata to delineate its transcriptional responses during macrophage infection in high temporal resolution. RNAPII profiles revealed dynamic C. glabrata responses to macrophages with genes of specialized pathways activated chronologically at different times of infection. We identified an uncharacterized transcription factor (CgXbp1) important for the chronological macrophage response, survival in macrophages, and virulence. Genome-wide mapping of CgXbp1 direct targets further revealed its multi-faceted functions, regulating not only virulence-related genes but also genes associated with drug resistance. Finally, we showed that CgXbp1 indeed also affects fluconazole resistance. Overall, this work presents a powerful approach for examining host-pathogen interaction and uncovers a novel transcription factor important for C. glabrata’s survival in macrophages and drug tolerance.